As brands pour more of their advertising budgets into measurable online performance marketing, it becomes increasingly important to understand in detail, the influence an ad has on a customer, and the 'value' of customers each online performance partner drives.
Within performance marketing, determining these answers requires brands to step back and look at both big picture objectives, as well as drill deep into their data - beyond the simple click. Value attribution is a click path analysis model that brands should look at to understand the exact role different partners play in the path to sale and ultimately uncover better insights into customer behavior.
An analogy is for a brand to think about all of the partner sites where its ads run the same way an individual thinks about their retirement portfolio. It's made up of stocks, bonds, cash and other investments that individually create different levels of value based on end objectives. Just as investors need to look deep into their investment data to know where to focus and shift resources, brands need to look into their partner data to do the same.
Value attribution provides a way for brands to understand the two things we mention at the start - ad influence and customer value. Knowing the influence a partner had in the path to sale enables brands to take control and make more informed decisions about who to reward, where to invest advertising dollars, and why. It also helps identify partners who win or lose disproportionately because of the 'last click wins' model, which is the status quo but flawed because it doesn't fully address influence and value.
The other half of the equation is customer value. Knowing the value of customers that each partner drives allows brands to identify what ads and promotions are working best for certain audiences. This can be based on factors such how much a customer spends (average order value) and whether customers are new or return. Armed with these insights, brands can then focus on maximizing opportunities and rewards for partners that drive and convert 'higher value' customers.
The key to all of this information ultimately lies in a brand's ability to track and measure their performance marketing data. This should take place on two levels for performance marketing managers whether handled in-house at a brand, by a digital agency, or a network. The first level is the more day-to-day data analysis that provides an overview of how partners perform over time and how a campaign performs over time per each partner.
Just like with daily stock movements for the investor, it's easy for brands to get absorbed in the day-to-day, view. However, they should ideally also be drilling into a deeper level of data to uncover 'unknown unknowns' about influence and customer value. As the volume, variety, and velocity of performance marketing data continues to increase, data management can become a pain point for brands. Today, tracking is facilitated by new technologies that brands can either build internally, or buy depending on specific needs, scale and depth to which they desire to analyze their data. To be effective, these technologies must ultimately become increasingly flexible, scalable and able to react to data as it happens.
Big data is a buzzword that still gets thrown around a lot. What defines it, as well as its usefulness is often a source of debate. Beyond the hype though, data-driven performance marketing will only continue to become more prevalent, as brands seek to maximize ROI based on more in-depth information. The question isn't whether the data exists or is available - brands can mine and generate all the data in the world. The real question is how the data can drive insight. Value attribution based on fine-grained data analysis is a model that ultimately benefits both brands engaged in performance marketing, as well as the partners who act as brand extensions in the online world.
Malcolm Cowley, CEO of Performance Horizon Group